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Guimarães Nobre G, Hunink JE, Baruth B, et al. Translating large-scale climate variability into crop production forecast in Europe. Sci Rep. 2019;9(1):1277doi: 10.1038/s41598-018-38091-4.
Guimarães Nobre, G., Hunink, J. E., Baruth, B., Aerts, J. C. J. H., & Ward, P. J. (2019). Translating large-scale climate variability into crop production forecast in Europe. Scientific reports, 9(1), 1277. https://doi.org/10.1038/s41598-018-38091-4
Guimarães Nobre, Gabriela, et al. "Translating large-scale climate variability into crop production forecast in Europe." Scientific reports vol. 9,1 (2019): 1277. doi: https://doi.org/10.1038/s41598-018-38091-4
Guimarães Nobre G, Hunink JE, Baruth B, Aerts JCJH, Ward PJ. Translating large-scale climate variability into crop production forecast in Europe. Sci Rep. 2019 Feb 04;9(1):1277. doi: 10.1038/s41598-018-38091-4. PMID: 30718693; PMCID: PMC6361969.
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Sci Rep. 2019 Feb 04;9(1):1277. doi: 10.1038/s41598-018-38091-4.

Translating large-scale climate variability into crop production forecast in Europe.

Scientific reports

Gabriela Guimarães Nobre, Johannes E Hunink, Bettina Baruth, Jeroen C J H Aerts, Philip J Ward

Affiliations

  1. Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands. [email protected].
  2. FutureWater, Cartagena, Spain.
  3. Directorate Sustainable Resources, European Commission, Joint Research Centre, Ispra, Italy.
  4. Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands.

PMID: 30718693 PMCID: PMC6361969 DOI: 10.1038/s41598-018-38091-4

Abstract

Studies show that climate variability drives interannual changes in meteorological variables in Europe, which directly or indirectly impacts crop production. However, there is no climate-based decision model that uses indices of atmospheric oscillation to predict agricultural production risks in Europe on multiple time-scales during the growing season. We used Fast-and-Frugal trees to predict sugar beet production, applying five large-scale indices of atmospheric oscillation: El Niño Southern Oscillation, North Atlantic Oscillation, Scandinavian Pattern, East Atlantic Pattern, and East Atlantic/West Russian pattern. We found that Fast-and-Frugal trees predicted high/low sugar beet production events in 77% of the investigated regions, corresponding to 81% of total European sugar beet production. For nearly half of these regions, high/low production could be predicted six or five months before the start of the sugar beet harvesting season, which represents approximately 44% of the mean annual sugar beet produced in all investigated areas. Providing early warning of crop production shortages/excess allows decision makers to prepare in advance. Therefore, the use of the indices of climate variability to forecast crop production is a promising tool to strengthen European agricultural climate resilience.

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